Preprint Article Version 1 This version is not peer-reviewed

Combining Decision Support Approaches for Optimizing the Selection of Bundles of Ecosystem Services

Version 1 : Received: 24 May 2018 / Approved: 24 May 2018 / Online: 24 May 2018 (10:35:18 CEST)

A peer-reviewed article of this Preprint also exists.

Marto, M.; Reynolds, K.M.; Borges, J.G.; Bushenkov, V.A.; Marques, S. Combining Decision Support Approaches for Optimizing the Selection of Bundles of Ecosystem Services. Forests 2018, 9, 438. Marto, M.; Reynolds, K.M.; Borges, J.G.; Bushenkov, V.A.; Marques, S. Combining Decision Support Approaches for Optimizing the Selection of Bundles of Ecosystem Services. Forests 2018, 9, 438.

Journal reference: Forests 2018, 9, 438
DOI: 10.3390/f9070438

Abstract

This study examines the potential of combining decision support approaches to identify optimal bundles of ecosystem services. A forested landscape, Zona de Intervenção Florestal of Paiva and Entre-Douro and Sousa (Portugal), is used to test and demonstrate this potential. The landscape extends over 14,000 ha, representing 1,976 stands. The property is fragmented into 376 holdings. The overall analysis was performed in three steps. First, we selected six alternative solutions (A to F) in a Pareto frontier generated by a multiple criteria method within a decision support system (SADfLOR) for subsequent analysis. Next, an aspatial strategic multi-criteria decision analysis (MCDA) analysis was performed with the Criterium DecisionPlus (CDP) component of another decision support system (EMDS) to assess the aggregate performance of solutions A to F for the entire forested landscape with respect to their utility for delivery of ecosystem services. For the CDP analysis, SADfLOR data inputs were grouped into two sets of primary criteria: Wood Harvested and Other Ecosystem Services. Finally, a spatial logic-based assessment of solutions A to F for individual stands of the study area was performed with the NetWeaver component of EMDS. The NetWeaver model was structurally and computationally equivalent to the CDP model, but the key NetWeaver metric is a measure of the strength of evidence that solutions for specific land stands were optimal for the unit. Solutions D and B performed best in the aspatial strategic MCDA analysis, and a composite of the maps generated by NetWeaver demonstrated the spatial basis for the performance of solutions D and B in individual land stands. We conclude with a discussion of how the combination of decision support approaches encapsulated in the two systems could be further automated.

Subject Areas

decision support; multi-criteria decision analysis; multiple criteria pareto frontier methods; criterium decision plus; net weaver developer; SADfLOR; ecosystem management decision support system

Readers' Comments and Ratings (0)

Leave a public comment
Send a private comment to the author(s)
Rate this article
Views 0
Downloads 0
Comments 0
Metrics 0
Leave a public comment

×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.